Electromyogram (EMG) signal generated by voluntary contraction of muscles is often used in rehabilitation devices because of its distinct output characteristics compared to other bio-signals. This paper proposes a wearable EMG-based human-computer interface (HCI) for electric-powered wheelchair users with motor disabilities by C4 or C5 level spinal cord injury. User expresses his intention as shoulder elevation gestures, which are recognized by comparing EMG signals acquired from the levator scapulae muscles with a preset threshold value. In this paper HCI command to control electric-powered wheelchair is made of combinations of left-, right-and both-shoulders elevation gestures. The proposed wearable HCI hardware consists of two active surface electrodes, a high-speed micro-controller, a Bluetooth module, and a battery. Experimental results using the wearable EMG based HCI and the electric-powered wheelchair developed show the proposed wearable EMG-based HCI is feasible for the users with severe motor disabilities.

This paper proposes a novel real-time EMG pattern recognition for the control of a multifunction myoelectric hand from four channel EMG signals. To cope with the nonstationary signal property of the EMG, features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a linear-nonlinear feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. We implement a real-time control system for a multifunction myoelectric hand. From experimental results, we show that all processes, including myoelectric hand control, are completed within 125 msec, and the proposed method is applicable to real-time myoelectric hand control without an operation time delay.